Cerebral White Matter Connectivity in Adolescent Idiopathic Scoliosis: A Diffusion Magnetic Resonance Imaging Study.
David C Noriega-GonzalezJesús CrespoFrancisco ArduraJuan Calabia-Del CampoCarlos Alberola-LopezRodrigo de Luis-GarcíaAlberto Caballero-GarcíaAlfredo CórdovaPublished in: Children (Basel, Switzerland) (2022)
Adolescent idiopathic scoliosis (AIS) is characterized by the radiographic presence of a frontal plane curve, with a magnitude greater than 10° (Cobb technique). Diffusion MRI can be employed to assess the cerebral white matter. The aim of this study was to analyze, by means of MRI, the presence of any alteration in the connectivity of cerebral white matter in AIS patients. In this study, 22 patients with AIS participated. The imaging protocol consisted in T1 and diffusion-weighted acquisitions. Based on the information from one of the diffusion acquisitions, a whole brain tractography was performed with the MRtrix tool. Tractography is a method to deduce the trajectory of fiber bundles through the white matter based on the diffusion MRI data. By combining cortical segmentation with tractography, a connectivity matrix of size 84 × 84 was constructed using FA (fractional anisotropy), and the number of streamlines as connectomics metrics. The results obtained support the hypothesis that alterations in cerebral white matter connectivity in patients with adolescent idiopathic scoliosis (AIS) exist. We consider that the application of diffusion MRI, together with transcranial magnetic stimulation neurophysiologically, is useful to search the etiology of AIS.
Keyphrases
- white matter
- magnetic resonance imaging
- multiple sclerosis
- contrast enhanced
- diffusion weighted
- subarachnoid hemorrhage
- transcranial magnetic stimulation
- diffusion weighted imaging
- randomized controlled trial
- end stage renal disease
- chronic kidney disease
- high frequency
- high resolution
- healthcare
- mass spectrometry
- cerebral ischemia
- newly diagnosed
- brain injury
- prognostic factors
- resting state
- machine learning
- patient reported outcomes
- health information
- convolutional neural network
- wastewater treatment
- data analysis